1 Brief description

Models were rerun for measles, rubella, meningitis A, Hepatitis B, HPV and yellow fever. Four scenarios were run: no-vaccination, default-update, default-update-catchup, default-nocovid. The impacts were calculated generally as:

default_nocovid = novax - default_nocovid,

default_update = novax - default_update,

default_catchup = default_update - default_update_catchup,

but we also consider default_nocovid-default_update. The time period we consider is 2020 to 2030.

2 Where has the 2020-21 disruption left us?

3 What can be done to mitigate losses in coverage

3.1 Headline figures

3.1.1 Tables

Catch-up activities as we have modelled them would avert 18321 (95%[6246, 58522], 80%[7321, 38465], 50%[9261, 23029]) med =12485 deaths between calendar years 2020-2030 and 111530 (95%[90458, 148304], 80%[96155, 131645], 50%[101994, 117811]) med =109300 between birth cohorts 2020-2030.

This represents 37.54% (95%[16.73%, 61.49%]) med=37.04 of excess deaths between calendar years 2020 and 2030 [numerator 18321 (95%[6246, 58522]) med=12485, denominator 49119 (95%[17248, 134941]) med=34713] due to disruptions or 78.9% (95%[40.36%, 151.35%]) med=76.37 of excess deaths between calendar years 2023 and 2030 [numerator 18900 (95%[7037, 60223]) med=13029, denominator 25356 (95%[9859, 75073]) med=15856].

4 Full uncertainty figures

4.1 cross

Highlighted if median is greater than 200 at any point, only figures where the abs(median) excess is >50 are included.

Highlighted if median is greater than 200 at any point, only figures where the abs(median) excess is >50 are included.

Highlighted if median is greater than 200 at any point, only figures where the abs(median) excess is >50 are included.

Highlighted if median is greater than 200 at any point, only figures where the abs(median) excess is >50 are included.

5 Interim update

In this section we perform a simple interim update on the covidimpactiu touchstone.

5.1 Overall differences

We present the percentage difference to the default-update baseline over the entire time period 2020:2030 for each scaling of the potential routine-intensified impact ratio.

5.2 What is the breakdown of excess deaths by year and activity type?

We estimate that in the absence of COVID-related disruptions, with conservative targets by 2030, there will be 37,378,194 (95%[34,450,249, 40,241,202]) deaths averted over the decade, so 3,737,819 (95%[3,445,025, 4,024,120]) on average a year. In contrast, with COVID-related disruptions and recovery, we estimate that 36,410,559 (95%[33,515,397, 39,241,799]) will be averted over the decade, so 3,641,056 (95%[3,351,540, 3,924,180]) on average a year. This is a difference of 2.66 (95%[2.52, 2.81])%. We may also consider this by country, below.

Of the deaths averted over the decade, and the excess deaths due to coverage disruptions, 3.64 (95%[2.65, 4.82])% is due to differences in campaigns and 96.36 (95%[95.18, 97.35])% is due to routine differences. The breakdown is shown below.

6 All disease stacked bar